Publications by authors named "Wenfeng Kang"

The Asian citrus psyllid (ACP), Diaphorina citri, serves as the primary vector for Candidatus Liberibacter asiaticus (CLas), the pathogen responsible for citrus Huanglongbing (HLB). D. citri modulates the expression of its key proteins in response to CLas infection.

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Background: Medulloblastoma is the most common malignant pediatric brain tumor and group 3 subtype medulloblastoma (G3-MB) exhibits the worst prognosis. Super enhancers (SEs) are large clusters of enhancers that play important roles in cancer through transcriptional control of cell identity genes, oncogenes and tumor-dependent genes. Dissecting SE-driven transcriptional dependencies of cancer leads to identification of novel oncogenic mechanisms, therapeutic strategies and targets.

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Background: Lung cancer is one of the leading causes of cancer mortality worldwide. Here, we performed an integrative bioinformatics analysis to screen hub genes and critical pathways in non-small cell lung cancer (NSCLC) based on the overall survival rate of differentially expressed genes (DEGs).

Methods: Four datasets from the gene expression omnibus (GEO) were used to identify the DEGs.

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Germline deletion of the p53 gene in mice gives rise to spontaneous thymic (T-cell) lymphomas. In this study, the p53 knockout mouse was employed as a model to study the mutational evolution of tumorigenesis. The clonality of the T-cell repertoire from p53 knockout and wild-type thymic cells was analyzed at various ages employing TCRβ sequencing.

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The Li-Fraumeni syndrome (LFS) and its variant form (LFL) is a familial predisposition to multiple forms of childhood, adolescent, and adult cancers associated with germ-line mutation in the TP53 tumor suppressor gene. Individual disparities in tumor patterns are compounded by acceleration of cancer onset with successive generations. It has been suggested that this apparent anticipation pattern may result from germ-line genomic instability in TP53 mutation carriers, causing increased DNA copy-number variations (CNVs) with successive generations.

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Background: Drug interactions can have a significant impact on the response to combinatorial therapy for anticancer treatment. In some instances these interactions can be anticipated based on pre-clinical models. However, the anticipation of drug interactions in the clinical context is in general a challenging task.

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